Systems and methods are disclosed. A digitized human vocal expression of a user and digital images are received over a network from a remote device. The digitized human vocal expression is processed to determine characteristics of the human vocal expression, including: pitch, volume, rapidity, a magnitude spectrum identify, and/or pauses in speech. Digital images are received and processed to detect characteristics of the user face, including detecting if any of the following is present: a sagging lip, a crooked smile, uneven eyebrows, and/or facial droop. Using the human vocal expression characteristics and face characteristics, a determination is made as to what action is to be taken. A cepstrum pitch may be determined using an inverse Fourier transform of a logarithm of a spectrum of a human vocal expression signal. The volume may be determined using peak heights in a power spectrum of the human vocal expression.

A driver assistance device includes an image analysis part that analyzes a captured image obtained by capturing a face of a driver of a vehicle, and an abnormality determination processing part that determines whether a state of the driver is in an abnormal state on the basis of an analysis result of the captured image, and performs an emergency driving stop process of causing the vehicle to perform automatic braking if the driver's state is determined to be in the abnormal state. The abnormality determination processing part does not perform the emergency driving stop process when the level of recognition of the face of the image analysis part is lower than the predetermined level.

An information collection unit collects information indicating a driving operation of a vehicle by a driver and a state of the vehicle changed by the driving operation, and outputs, among the collected information, information in a period from a start point at which a driving operation contributing to stop of the vehicle is performed to a stop start point in a stop state where a stop time of the vehicle continues for a predetermined time or more, as driving operation information. A state estimation unit acquires driver state information indicating a state of the driver from a learned learner on which machine learning has been performed so as to output the driver state information when the driving operation information is input, by inputting the driving operation information output from the information collection unit to the learner and performing arithmetic processing of the learner.

An in-vehicle apparatus (1) according to the present disclosure includes: estimated walking path acquisition means (21) for acquiring an estimated walking path, which is a path in which it is estimated that a driver will walk; and drinking determination means (22) for determining whether or not the driver is drunk based on a walking pattern of the driver in the estimated walking path.

This disclosure relates to a system and method for transitioning vehicle control between autonomous operation and manual operation. The system includes sensors configured to generate output signals conveying information related to the vehicle and its operation. During autonomous vehicle operation, the system gauges the level of responsiveness of a vehicle operator through challenges and corresponding responses. The system determines when to present a challenge to the vehicle operator based on internal and external factors. If necessary, the system will transition from an autonomous operation mode to a manual operation mode.

A driver assistance system for vehicles, which is capable of preventing driver carelessness from causing a vehicle accident when a vehicle stops while traveling, includes a vehicle sensor unit configured to detect driver state data, a driver assistance unit operated to assist a driver when driver carelessness about vehicle driving is detected when a vehicle stops while traveling, and a control unit configured to identify whether the driver is careless based on the driver state data when the vehicle stops while traveling, and to operate the driver assistance unit when the driver carelessness is detected, preventing the vehicle from driving.

Driving support ECU transmits a communication connection request to a help net center HNC when a driver of a vehicle has been determined to be in an abnormal state where the driver loses an ability to drive the vehicle, and when the communication connection to the help net center HNC has been established, the driving support ECU transmits the help signal (the positional information of the vehicle) and decelerates the vehicle at a constant deceleration to make the vehicle stop. On the other hand, when the communication connection to the help net center HNC has not been established, the driving support ECU makes the vehicle travel at a constant speed. Accordingly, it is possible to make the vehicle stop under a situation where the help net center HNC recognizes the vehicle position inside which the driver who has been determined to be in the abnormal state is.

Driving support ECU transmits a communication connection request to a help net center HNC when a driver of a vehicle has been determined to be in an abnormal state where the driver loses an ability to drive the vehicle, and when the communication connection to the help net center HNC has been established, the driving support ECU transmits the help signal (the positional information of the vehicle) and decelerates the vehicle at a constant deceleration to make the vehicle stop. On the other hand, when the communication connection to the help net center HNC has not been established, the driving support ECU makes the vehicle travel at a constant speed. Accordingly, it is possible to make the vehicle stop under a situation where the help net center HNC recognizes the vehicle position inside which the driver who has been determined to be in the abnormal state is.

A hands-on determination device, a system including the same, and a vehicle control method thereof are provided. The hands-on determination device includes a processor that determines a hands-on state of a driver through motion recognition and determines whether to use a result of determination of the hands-on state based on at least one of a weather condition, a condition for validity of motion sensing, classification of a driving road, a vehicle control state, or a driver state and a storage storing data for motion recognition.

A driver assistance device includes an image analysis part that analyzes a captured image obtained by capturing a face of a driver of a vehicle, an abnormality determination processing part that determines whether a state of the driver is an abnormal state on the basis of an analysis result of the captured image and performs an emergency driving stop process of causing the vehicle to perform automatic braking when the driver is determined to be in the abnormal state, and a cancellation detection part that detects a cancellation which the driver makes to cancel an execution of the emergency driving stop process. If the cancellation detection part detects the cancellation within a predetermined time period from when the emergency driving stop process starts, the abnormality determination processing part does not perform the next emergency driving stop process.